1. Technical Field
This application generally relates to machine learning, and more particularly to machine learning techniques used in connection with ranking sets of data.
2. Description of Related Art
Data may be stored in an electronic form for use with computerized techniques. A large amount of computerized data used in connection with a variety of different applications presents a challenge for how to locate and organize relevant information. Once a set of relevant data has been determined, a problem exists of how to order or rank the identified relevant data. As an example, a user may perform a search, such as using a search engine for relevant web pages. The query may result in a set of web pages which are relevant to the user's query terms. The user may not simply want a listing of the result set and may want to know what elements of the result set are the most relevant in accordance with the user query. Furthermore, the resulting query set may be large making a task of determining the most relevant information for the particular query more difficult for the user as the size of the resulting query set increases.
Machine learning techniques may be used in connection with ranking data sets such as the foregoing resulting query set. Existing machine learning techniques operate on vector-valued data to learn a ranking function inducing a ranking or ordering. However, input data may not be vector-valued data and, thus, may not utilize existing techniques for ranking.